Apprentices in Ontario: Who Pursues Apprenticeships and What Are Their Pathways into and out of Various PSE Institutions and the Labour Market?

Authors
Elena Hillman
Taylor Noriko Paul
Michael Haan
Wolfgang Lehmann
Reference Number
R2138
Date
Status
Abstract

An important and under-researched aspect of developing a skilled workforce in Canada are the pathways taken by students into and out of PSE and apprenticeships, and, more specifically, how student mobility factors into completion rates. Drawing on Statistics Canada’s Education and Labour Market Longitudinal Platform (ELMLP), this research project analyzes the students who pursue apprenticeships; what lateral and vertical transfer pathways students take into and out of various postsecondary education (PSE) institutions in Ontario; and the sequencing of these transfers. In addition, this study examines the destinations of individuals exiting apprenticeship programs, including vertical transfers into other apprenticeship programs, divergent transfers into colleges and/or university programs, and direct-entry into the labour market. 

Key Findings

  • Most apprentices do not transfer from another type of postsecondary education program.
  • A substantial number of apprentices are non-visible minority, native-born men who are between the ages of 15 to 24.
  • Not only are major trades groups gender segregated, but a higher number of visible minority apprentices study female dominated trades.
  • While most enter into apprenticeships through employment, many end up re-entering the labour market without completing their apprenticeship training.
  • After that, the second most common pathway is from employment to completion of apprenticeship training to employment again.
  • Those who switch their program of study earn less than those who do not switch, suggesting that they either transferred to a lower-paying program, or that they may have encountered barriers during the transition.
  • The results also illustrate a significant gender pay gap that is not explained by the covariates in the model. This suggests that factors other than gender segregation in the skilled trades and age impact the pay differential between men and women.